# Match the weapons to respective gun types
# Categorise gun types using dictionaries
# key - gun type, value - weapon names
gun_categories = {
'Assault Rifles':['AKM','M16A4','SCAR-L','M416','Groza','M762'],
'Lever Action Sniper Rifles':['Kar98K','M24','AWM'],
'Automatic Snifer Rifles':['SKS','VSS','Mini 14','Mk14','SLR'],
'SubMachine Guns':['Micro UZI','UMP9','Vector','Tommy Gun'],
'Shotguns':['S686','S1897','S12K'],
'Light Machine Guns':['M249','DP-28'],
'Pistols':['P92','P1911','R1895','P18C']
}
# Define a mapping function
# the parameter 'weapon' represents the value in the column "Weapons"
# the function then iterates (performs repeatedly) over the items of the gun_categories dictionary using the .items() method
# 'gun_categories' dict - key: gun types, value: weapon names
# in the loop, if 'weapon' presents in the 'value' list (weapon names) in the dict
# means the 'weapon' belongs to the gun type, the corresponding 'key' is returned
# if no match is found, the function returns 'None'
def map_gun_type(weapon):
for key, values in gun_categories.items():
if weapon in values:
return key
return None
# Map values using the mapping function
top15_df["Gun type"] = top15_df["Weapons"].map(map_gun_type)
# Use the same way to match the weapons to respective ammo types
# Categorise gun types using dictionaries
# key - ammo type, value - weapon names
ammo_categories = {'.300 Magnum Ammo':'AWM',
'.45 ACP Ammo':['P1911','Tommy Gun','UMP9'],
'12 Gauge Ammo':['S1897','S686','S12K'],
'5.56mm Ammo':['M16A4','M249','M416','SCAR-L','Mini 14'],
'7.62mm Ammo':['AKM','DP-28','Groza','M762','Kar98K','M24','Mk14','R1895','SKS','SLR'],
'9mm Ammo':['Micro UZI','P92','VSS','P18C','Vector']
}
# Define a mapping function
# the parameter 'weapon' represents the value in the column "Weapons"
# the function then iterates (performs repeatedly) over the items of the ammo_cat dictionary using the .items() method
# 'ammo_cat' dict - key: ammo types, value: weapon names
# in the loop, if 'weapon' presents in the 'value' list (weapon names) in the dict
# means the 'weapon' belongs to the gun type, the corresponding 'key' is returned
# if no match is found, the function returns 'None'
def map_ammo_type(weapon):
for key, values in ammo_categories.items():
if weapon in values:
return key
return None
# Map values using the mapping function
top15_df["Ammo type"] = top15_df["Weapons"].map(map_ammo_type)
# let the index starts from 1 (instead of 0)
top15_df.index = range(1, len(top15_df) + 1)
# Show the final list of Top 15 Weapons, followed by Gun and Ammo type
top15_df
